Trying to view decision tree in my notebook
I am trying to scale my decision tree to fit notebook but it appears not to scale properly. I have to keep scrolling for a better view. Can I please have some help on how to fix this. Attach is a pic of how it looks like.
from graphviz import Source
from sklearn import tree
from IPython.display import SVG
graph = Source( tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
SVG(graph.pipe(format='svg'))
pandas machine-learning scikit-learn graphviz
asked Apr 11 at 5:06
Kwesi Gene
397
add a comment |
I am trying to scale my decision tree to fit notebook but it appears not to scale properly. I have to keep scrolling for a better view. Can I please have some help on how to fix this. Attach is a pic of how it looks like.
from graphviz import Source
from sklearn import tree
from IPython.display import SVG
graph = Source( tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
SVG(graph.pipe(format='svg'))
pandas machine-learning scikit-learn graphviz
asked Apr 11 at 5:06
Kwesi Gene
397
add a comment |
I am trying to scale my decision tree to fit notebook but it appears not to scale properly. I have to keep scrolling for a better view. Can I please have some help on how to fix this. Attach is a pic of how it looks like.
from graphviz import Source
from sklearn import tree
from IPython.display import SVG
graph = Source( tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
SVG(graph.pipe(format='svg'))
pandas machine-learning scikit-learn graphviz
asked Apr 11 at 5:06
Kwesi Gene
397
I am trying to scale my decision tree to fit notebook but it appears not to scale properly. I have to keep scrolling for a better view. Can I please have some help on how to fix this. Attach is a pic of how it looks like.
from graphviz import Source
from sklearn import tree
from IPython.display import SVG
graph = Source( tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
SVG(graph.pipe(format='svg'))
pandas machine-learning scikit-learn graphviz
pandas machine-learning scikit-learn graphviz
asked Apr 11 at 5:06
Kwesi Gene
397
asked Apr 11 at 5:06
Kwesi Gene
397
asked Apr 11 at 5:06
Kwesi Gene
397
asked Apr 11 at 5:06
Kwesi Gene
397
asked Apr 11 at 5:06
Kwesi Gene
397
397
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = ""15,15"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
answered Nov 13 at 11:49
Germán Sanchis
512
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f49766875%2ftrying-to-view-decision-tree-in-my-notebook%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = ""15,15"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
answered Nov 13 at 11:49
Germán Sanchis
512
add a comment |
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = ""15,15"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
answered Nov 13 at 11:49
Germán Sanchis
512
add a comment |
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = ""15,15"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
answered Nov 13 at 11:49
Germán Sanchis
512
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = ""15,15"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
answered Nov 13 at 11:49
Germán Sanchis
512
answered Nov 13 at 11:49
Germán Sanchis
512
answered Nov 13 at 11:49
Germán Sanchis
512
answered Nov 13 at 11:49
Germán Sanchis
512
512
add a comment |
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f49766875%2ftrying-to-view-decision-tree-in-my-notebook%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
